I think they should be "one of" not "the one." You know, it takes a village. And in any event, as others have said, parents have completely refused to participate in the question anyways, so in the real world your statement is not worth the paper it's written on.
The point is that the next token predicted will change; and in a way everyone not being a anti-ai contrarian will say is smarter. And as far as TFA, we've know you can prompt models into being smarter for years know. Thats what CoT/thinking/reasoning is.
Ive held a long belief that sports fans are a main demographic that has allowed enshittification of tv to happen. Without you guys eating this up and asking for more where would we be?
We’d have, say, 20 or 30 seasons of shows that are well past their prime, because the ad breaks are really profitable. Grey’s Anatomy and The Simpsons come to mind.
No, not really. This has been telegraphed for a long time by everyone involved. HN denizens have been unashamedly anti-ai for years now, so what makes sense is the not knowing part of this audience. Chinese models are also not frontier models.
I still find it baffling how the idea that HN is "unashamedly anti-ai" gets repeated.
Every single model release gets submitted within minutes of an announcement and frequently break 1000+ points within an hour or two. Blog posts about vibe coding or the current flavor of harness/workflow/tool are constantly making the front page. Karpathy's latest writing/presentations or "Learn how LLMs work using X" are perennial front page content.
There were moments in 2023/2024 where all but a handful of posts on the front page were about AI (and not the Reddit r/popular "residents worried about infrasound and EM radiation near new datacenter" variety).
For example, the responses to this very recent post were overwhelmingly praising Gen AI's capabilities:
Ask HN: What was your "oh shit" moment with GenAI?
There are counter examples of course but just because HN isn't exclusively AI hype at all times doesn't mean it's "unashamedly anti-AI".
I honestly can't think of any single topic other than the Snowden leaks in 2013/2014 that even comes close to dominating HN discussion like LLMs/GenAI from 2022 to present.
data centers with evap cooling use a lot of water and in some places its taking away from residents. thats a fact not a conspiracy. closed loop systems exist and its possible to make them mandatory by law or city ordinance, but if they did that the company running the data center would make a little less money so they act like pumping out water is the only way. its the same with carbon emissions and making them build solar panels.
That's a good default position, and I think should be our starting point.
But the devil is in the details. If we don't want advertisers constructing semi-complete profiles from simple web interactions then why would we publish 330 million census questionnaires for their use?
At some point you have to say "Is not having it better than having it?" Where's your dude, today, who's gonna code this? If it were gone happen, it wouldve.
> This is the supply that a sufficiently powerful quantum attacker could steal by inverting ECDSA/Schnorr signatures
While I only read approximately one more sentence than you did of tfa, I would also like to know what "sufficiently powerful" means and why we don't want public keys to be public
It's well known that people veer when they walk. That's a reason why people die in the wilderness after they get lost, because they walk around in circles going no where
Google is clearly gimping the gemma models. There is a 122b gemma 4 that was never released, but was a part of the announcement tweet. Plus they weren't going to release MTP until people figured out they're running it on the pixels
I dunno about that. Gemma 4 is probably the best model for general self-hosted use for almost everyone that doesn't have a data center in their basement. They didn't have to release it at all, and they didn't have to release speculative decoding drafters, and they didn't have to release the QAT version of the models that makes the 4-bit quantization perform very close to the bigger versions, and can run in 32GB. I'd love a 122B version of it, and I didn't realize they'd ever announced one was coming (though I remember there being speculation about it). But, also, I'm happy they're doing so much with it. They've got all the sizes covered, it has great prose for an LLM, better prose than even most larger models, it's got great audio and vision, and broad language support. As self-hosted general purpose models go, it's the total package.
Qwen 3.6 is maybe better for code (though I'm beginning to think otherwise after some benchmarking I've been doing, where Gemma 4 has been overperforming expectations), but for just about anything else, Gemma 4 is the one.
If they're gimping it, why is nobody else making a better one that small?
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